Clinicians are Outperformed by a Deep Learning System When Identifying Optic Disc Lesions

Update Item Information
Identifier 20220213_nanos_posters_233
Title Clinicians are Outperformed by a Deep Learning System When Identifying Optic Disc Lesions
Creator Dan Milea; Caroline Vasseneix; Simon Nusinovici; Xinxing Xu; Jeong-Min Hwang; Steffen Hamann; John Chen; Jing Liang Loo; Leonard Milea; Kenneth Boon Kiat Tan; Daniel Shu Wei Ting; Yong Liu; Nancy Newman; Valerie Biousse; Tien Yin Wong; Raymond Najjar; on behalf of the BONSAI Consortium
Affiliation (DM) (CV) (SN) (DSWT) (RN) Singapore Eye Research Institute, Singapore, Singapore; (XX) (YL) ASTAR Singapore, Singapore, Singapore; (JH) Bundang Hospital, Seoul, South Korea, Seoul, Republic of Korea; (SH) Rigshospitalet, Copenhagen, Denmark, Copenhagen, Denmark; (JC) Mayo Clinic, Rochester, Minnesota; (JLL) (TYW) Singapore National Eye Centre, Singapore, Singapore; (LM) University of California, Berkeley, California, USA, Berkeley, California; (KBKT) Singapore General Hospital, Singapore, Singapore; (NN) (VB) Emory University School of Medicine, Atlanta, USA, Atlanta, Georgia, USA; (BONSAI) BONSAI Consortium, BONSAI, Singapore
Subject High Intracranial Pressure/headache; Optic Neuropathy; Pseudotumor Cerebri; Vascular Disorders
Description Detection of optic disc abnormalities using ophthalmoscopy is a difficult task for non-ophthalmologists. We recently developed a deep learning system (BONSAI-DLS) to accurately classify optic discs on digital fundus photographs. The aim of this study was to compare the performance of the BONSAI-DLS to that of clinicians with or without ophthalmic training for the classification of optic discs.
Date 2022-02
Language eng
Format application/pdf
Type Text
Source 2022 North American Neuro-Ophthalmology Society Annual Meeting
Relation is Part of NANOS Annual Meeting 2022: Poster Session I: New Diagnostic Measurement Techniques
Collection Neuro-ophthalmology Virtual Education Library: NOVEL http://NOVEL.utah.edu
Publisher Spencer S. Eccles Health Sciences Library, University of Utah
Holding Institution North American Neuro-Ophthalmology Association. NANOS Executive Office 5841 Cedar Lake Road, Suite 204, Minneapolis, MN 55416
Rights Management Copyright 2022. For further information regarding the rights to this collection, please visit: https://NOVEL.utah.edu/about/copyright
ARK ark:/87278/s617h988
Context URL The NANOS Annual Meeting Neuro-Ophthalmology Collection: https://novel.utah.edu/collection/NAM/toc/
Setname ehsl_novel_nam
ID 2065051
Reference URL https://collections.lib.utah.edu/ark:/87278/s617h988
Back to Search Results